Applied mathematician and financial engineer interested in quantitative finance, numerical methods, artificial intelligence, and high-performance computing.
I enjoy understanding systems from first principles and often build tools myself to explore models, algorithms, and data.
- Quantitative finance and asset pricing
- Stochastic models and derivatives
- Numerical methods and scientific computing
- Artificial intelligence and reinforcement learning
- High-performance computing
- Systems programming
| Language | Experience |
|---|---|
| Rust | Exploring systems programming and building high-performance tools |
| Mojo | Developing numerical and data-science tooling with a focus on performance |
| Python | Data science, machine learning, and quantitative finance projects |
| MATLAB | Numerical methods, optimization, and engineering simulations |
| R | Statistical analysis and financial modeling |
| SQL | Data querying and database work |
- Building numerical and scientific computing tools in Rust and Mojo
- Implementing financial models and simulations from scratch
- Exploring reinforcement learning and AI methods for decision and optimization problems
- Studying performance-oriented machine learning systems
- Monte Carlo methods
- Option pricing and stochastic calculus
- Reinforcement learning and decision processes
- Neural networks and optimization
- Performance-focused numerical libraries
I’m always interested in discussing quantitative finance, numerical methods, AI, and high-performance computing.
If you’re working on interesting problems in these areas, feel free to connect.